Performance analysis and optimization of reciprocating compressor with stepless capacity control system under variable load conditions

2018 ◽  
Vol 94 ◽  
pp. 174-185 ◽  
Author(s):  
Yao Wang ◽  
Zhinong Jiang ◽  
Jinjie Zhang ◽  
Chao Zhou ◽  
Wenhua Liu
Keyword(s):  
Control System ◽  
Performance Analysis ◽  
Variable Load ◽  
Reciprocating Compressor ◽  
Capacity Control ◽  
Load Conditions

Thermal performance analysis of reciprocating compressor with stepless capacity control system

2013 ◽  
Vol 54 (2) ◽  
pp. 380-386 ◽  
Author(s):  
Tang Bin ◽  
Zhao Yuanyang ◽  
Li Liansheng ◽  
Liu Guangbin ◽  
Wang Le ◽  
...  
Keyword(s):  
Control System ◽  
Performance Analysis ◽  
Thermal Performance ◽  
Reciprocating Compressor ◽  
Capacity Control

scholarly journals Optimization Design of Actuator Parameters in Multistage Reciprocating Compressor Stepless Capacity Control System Based on NSGA-II

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Zhinong Jiang ◽  
Chao Zhou ◽  
Yao Wang ◽  
Jinjie Zhang ◽  
Wenhua Liu ◽  
...  
Keyword(s):  
Control System ◽  
Multiobjective Optimization ◽  
Impact Velocity ◽  
Hydraulic System ◽  
Optimization Design ◽  
Reciprocating Compressor ◽  
Spring Stiffness ◽  
Capacity Control ◽  
Nsga Ii ◽  
The Impact

The capacity control system of reciprocating compressor has great significance for the contribution of energy conservation and emission reduction. The parameters of the actuator and hydraulic system within a reciprocating compressor stepless capacity control system play a decisive role in its control accuracy, mechanical reliability, and mechanical security. The actuators and hydraulic system parameters of the same stage are in conflict with each other. Therefore, the actuator and the multistage reciprocating compressor are studied here, specifically through multiobjective optimization using the Nondominated Sorting Genetic Algorithm (NSGA)-II. The multiobjective optimization design was performed on a two-dimensional (2D) reciprocating compressor test bench. When the spring stiffness of the first stage spring was 27358 N m−1, the spring stiffness of the second stage spring was 23315 N m−1, the inlet oil pressure was 296.62 N, the impact velocity of ejection was 0.4215 m s−1, and the total indicated power deviation was 12.05 kW; the objective functions were optimized. Compared with traditional parameters, the inlet oil pressure, spring stiffness, and impact velocity were all reduced. This parameter optimization design lays the foundations for global optimization designs for stepless capacity control systems.

scholarly journals Optimization Design of Actuator Parameters with Stepless Capacity Control System Considering the Effect of Backflow Clearance

2020 ◽  
Vol 10 (8) ◽  
pp. 2703
Author(s):  
Jinjie Zhang ◽  
Chao Zhou ◽  
Zhinong Jiang ◽  
Yao Wang ◽  
Xu Sun
Keyword(s):  
Mathematical Model ◽  
Control System ◽  
Good Effect ◽  
Reciprocating Compressor ◽  
Spring Stiffness ◽  
Objective Functions ◽  
Capacity Control ◽  
Hydraulic Force ◽  
The Impact ◽  
The Relationship

The actuator is the key to the stepless capacity control system of a reciprocating compressor. The coupling effect between the actuator and the reciprocating compressor was not considered in the traditional design, and the large design margin led to low system reliability, high cost and low safety. In this paper, a reciprocating compressor and actuator were taken as research objects. The backflow clearance of the suction valve was simulated by CFD (computational fluid dynamics), The relationship between backflow clearance and resultant gas force of the valve plate was discussed. By building a mathematical model of actuators considering backflow clearance and impact rebound, the relationship between the parameters of actuators was studied. Based on the mathematical model and CFD analysis, the hydraulic force and spring stiffness were taken as the design variables, the impact velocity of ejection or withdrawal and the backflow clearance were taken as objective functions, and the actuator parameters were optimized with NSGA-II (Non-dominated Sorting Genetic Algorithm – II). The optimization results show that when the backflow clearance is 0.0065 mm, the hydraulic force is 94.25 N, and the spring stiffness is 11,575.84 N/m, the objective functions are optimized, the parameters are significantly improved, and a good effect is achieved on the experimental table of a 2D reciprocating compressor.

Experimental research on dynamic response of capacity control system in reciprocating compressor

2013 ◽  
Vol 228 (2) ◽  
pp. 358-365 ◽  
Author(s):  
Zhao Yuanyang ◽  
Tang Bin ◽  
Liu Guangbin ◽  
Li Liansheng ◽  
Yang Huaide ◽  
...  
Keyword(s):  
Control System ◽  
Dynamic Response ◽  
Control Systems ◽  
Hydraulic Pressure ◽  
Reciprocating Compressor ◽  
Capacity Control ◽  
Inlet Valve ◽  
Spring Force ◽  
Downward Displacement ◽  
Operating Lifetime

The forces acting on the actuator used in a reciprocating capacity control system are analyzed in this article. The dynamic response of this system is influenced significantly by hydraulic pressure and reset spring force. The performance of dynamic response is tested under different hydraulic pressures and reset springs. The results show that the influence of reset spring force on the downward speed and displacement of actuator is more inconspicuous than the hydraulic pressure, but the reset speeds decrease obviously when the reset spring force is small (SPR2 and SPR3). The maximum downward displacement decreases and the consuming time increases with the decrease in the hydraulic pressure. The maximum downward speed of actuator decreases with the decrease in hydraulic pressure which influences the reliability and life of this system. Therefore, the performance of dynamic response and operating lifetime needs to be considered simultaneously during the design of partial stroke press-off inlet valve capacity control systems.

scholarly journals An Adaptive Model Predictive Voltage Control for LC-Filtered Voltage Source Inverters

2021 ◽  
Vol 11 (2) ◽  
pp. 704
Author(s):  
Hosein Gholami-Khesht ◽  
Pooya Davari ◽  
Frede Blaabjerg
Keyword(s):  
Control System ◽  
System Performance ◽  
State Space Model ◽  
Adaptive Observer ◽  
Voltage Source ◽  
Adaptive Model ◽  
Space Model ◽  
System Uncertainties ◽  
Augmented State ◽  
Load Conditions

The three-phase inductor and capacitor filter (LC)-filtered voltage source inverter (VSI) is subjected to uncertain and time-variant parameters and disturbances, e.g., due to aging, thermal effects, and load changes. These uncertainties and disturbances have a considerable impact on the performance of a VSI’s control system. It can degrade system performance or even cause system instability. Therefore, considering the effects of all system uncertainties and disturbances in the control system design is necessary. In this respect and to tackle this issue, this paper proposes an adaptive model predictive control (MPC), which consists of three main parts: an MPC, an augmented state-space model, and an adaptive observer. The augmented state-space model considers all system uncertainties and disturbances and lumps them into two disturbance inputs. The proposed adaptive observer determines the lumped disturbance functions, enabling the control system to keep the nominal system performance under different load conditions and parameters uncertainty. Moreover, it provides load-current-sensorless operation of MPC, which reduces the size and cost, and simultaneously improves the system reliability. Finally, MPC selects the proper converter voltage vector that minimizes the tracking errors based on the augmented model and outputs of the adaptive observer. Simulations and experiments on a 5 kW VSI examine the performance of the proposed adaptive MPC under different load conditions and parameter uncertainties and compare them with the conventional MPC.

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